The fall speeds of sub-100 mu m ice crystals

Estimates for the sedimentation rate of realistic ice crystals at sizes smaller than 100 µm are presented. These calculations, which exploit new results for the capacitance of ice crystals, are compared with laboratory studies and found to be in good agreement. The results highlight a weakness in contemporary ice particle fall speed parametrizations for very small crystals, which can lead to sedimentation rates being overestimated by a factor of two. The theoretical approach applied here may also be useful for calculating the sedimentation rate and mobility of non-spherical aerosol particles.

Acid-base reactions between an acidic soil and plant residues

The elemental composition of residues of maize (Zea mays), sorghum (S. bicolor), groundnuts (Arachis hypogea), soya beans (Glycine max), leucaena (L. leucocephala), gliricidia (G. sepium), and sesbania (S. sesban) was determined as a basis for examining their alkalinity when incorporated into an acidic Zambian Ferralsol. Potential (ash) alkalinity, available alkalinity by titration to pH 4 and soluble alkalinity (16 It water extract titrated to pH 4) were measured. Potential alkalinity ranged from 3 73 (maize) to 1336 (groundnuts) mmol kg(-1) and was equivalent to the excess of their cation charge over inorganic anion charge. Available alkalinity was about half the potential alkalinity. Cations associated with organic anions are the source of alkalinity. About two thirds of the available alkalinity is soluble. Residue buffer curves were determined by titration with H2SO4 to pH 4. Soil buffer capacity measured by addition of NaOH was 12.9 mmol kg(-1) pH(-1). Soil and residue (10 g:0.25 g) were shaken in solution for 24 h and suspension pH values measured. Soil pH increased from 4.3 to between 4.6 (maize) and 5.2 (soyabean) and the amounts of acidity neutralized (calculated from the rise in pH and the soil buffer capacity) were between 3.9 and 11.5 mmol kg(-1), respectively. The apparent base contributions by the residues (calculated from the buffer curves and the fall in pH) ranged between 105 and 350 mmol kg(-1) of residue, equivalent to 2.6 and 8.8 mmol kg(-1) of soil, respectively. Therefore, in contact with soil acidity, more alkalinity becomes available than when in contact with H2SO4 solution. Available alkalinity (to pH 4) would be more than adequate to supply that which reacts with soil but soluble alkalinity would not. It was concluded that soil Al is able to displace cations associated with organic anions in the residues which are not displaced by H+, or that residue decomposition may have begun in the soil suspension releasing some of the non-available alkalinity. Soil and four of the residues were incubated for 100 days and changes in pH, NH4+ and NO3- concentrations measured. An acidity budget equated neutralized soil acidity with residue alkalinity and base or acid produced by N transformations. Most of the potential alkalinity of soyabean and leucaena had reacted after 14 days, but this only occurred after 100 days for gliricidia, and for maize only the available alkalinity reacted. For gliricidia and leucaena, residue alkalinity was primarily used to react with acidity produced by nitrification. Thus, the ability of residues to ameliorate acidity depends not only on their available and potential alkalinity but also on their potential to release mineral N. (C) 2004 Elsevier B.V. All rights reserved.

Self-charging of the Eyjafjallajökull volcanic ash plume

Abstract Volcanic plumes generate lightning from the electrification of plume particles. Volcanic plume charging at over 1200 km from its source was observed from in situ balloon sampling of the April 2010 Eyjafjallajökull plume over Scotland. Whilst upper and lower edge charging of a horizontal plume is expected from fair weather atmospheric electricity, the plume over Scotland showed sustained positive charge well beneath the upper plume edge. At these distances from the source, the charging cannot be a remnant of the eruption itself because of charge relaxation in the finite conductivity of atmospheric air.

The rise and fall of open solar flux during the current grand solar maximum

We use geomagnetic activity data to study the rise and fall over the past century of the solar wind flow speed VSW, the interplanetary magnetic field strength B, and the open solar flux FS. Our estimates include allowance for the kinematic effect of longitudinal structure in the solar wind flow speed. As well as solar cycle variations, all three parameters show a long-term rise during the first half of the 20th century followed by peaks around 1955 and 1986 and then a recent decline. Cosmogenic isotope data reveal that this constitutes a grand maximum of solar activity which began in 1920, using the definition that such grand maxima are when 25-year averages of the heliospheric modulation potential exceeds 600 MV. Extrapolating the linear declines seen in all three parameters since 1985, yields predictions that the grand maximum will end in the years 2013, 2014, or 2027 using VSW, FS, or B, respectively. These estimates are consistent with predictions based on the probability distribution of the durations of past grand solar maxima seen in cosmogenic isotope data. The data contradict any suggestions of a floor to the open solar flux: we show that the solar minimum open solar flux, kinematically corrected to allow for the excess flux effect, has halved over the past two solar cycles.

Seasonal 'fall out' of sessile macro-fauna from submarine cliffs: quantification, causes and implications

Submarine cliffs are typically crowded with sessile organisms, most of which are ultimately exported downwards. Here we report a 24 month study of benthic fauna dropping from such cliffs at sites of differing cliff angle and flow rates at Lough Hyne Marine Nature Reserve, Co. Cork, Ireland. The magnitude of 'fall out' material collected in capture nets was highly seasonal and composed of sessile and mobile elements. Sponges, ascidians, cnidarians, polychaetes, bryozoans and barnacles dominated the sessile forms. The remainder (mobile fauna) were scavengers and predators such as asteroid echinoderms, gastropod molluscs and malacostracan crustaceans. These were probably migrants targeting fallen sessile organisms. 'Fall out' material (including mobile forms) increased between May and August in both years. This increase in 'fall out' material was correlated with wrasse abundance at the cliffs (with a one month lag period). The activities of the wrasse on the cliffs (feeding, nest building and territory defence) were considered responsible for the majority of 'fall out' material, with natural mortality and the activity of other large mobile organisms (e.g. crustaceans) also being triplicated. Current flow rate and cliff profile were important in amount of 'fall out' material collected. In low current situations export of fallen material was vertical, while both horizontal and vertical export was associated with moderate to high current environments. Higher 'fall out' was associated with overhanging than vertical cliff surfaces. The 'fall out' of marine organisms in low current situations is likely to provide ail important source of nutrition in close proximity to the cliff, in an otherwise impoverished soft sediment habitat. However, in high current areas material will be exported some distance from the source, with final settlement again occurring in soft sediment habitats (as current speed decreases).

Advancements in the estimation of ice particle fall speeds using laboratory and field measurements

Accurate estimates for the fall speed of natural hydrometeors are vital if their evolution in clouds is to be understood quantitatively. In this study, laboratory measurements of the terminal velocity vt for a variety of ice particle models settling in viscous fluids, along with wind-tunnel and field measurements of ice particles settling in air, have been analyzed and compared to common methods of computing vt from the literature. It is observed that while these methods work well for a number of particle types, they fail for particles with open geometries, specifically those particles for which the area ratio Ar is small (Ar is defined as the area of the particle projected normal to the flow divided by the area of a circumscribing disc). In particular, the fall speeds of stellar and dendritic crystals, needles, open bullet rosettes, and low-density aggregates are all overestimated. These particle types are important in many cloud types: aggregates in particular often dominate snow precipitation at the ground and vertically pointing Doppler radar measurements. Based on the laboratory data, a simple modification to previous computational methods is proposed, based on the area ratio. This new method collapses the available drag data onto an approximately universal curve, and the resulting errors in the computed fall speeds relative to the tank data are less than 25% in all cases. Comparison with the (much more scattered) measurements of ice particles falling in air show strong support for this new method, with the area ratio bias apparently eliminated.

Evaluating the structure and magnitude of the ash plume during the initial phase of the 2010 Eyjafjallajökull eruption using lidar observations and NAME simulations

The Eyjafjallajökull volcano in Iceland erupted explosively on 14 April 2010, emitting a plume of ash into the atmosphere. The ash was transported from Iceland toward Europe where mostly cloud-free skies allowed ground-based lidars at Chilbolton in England and Leipzig in Germany to estimate the mass concentration in the ash cloud as it passed overhead. The UK Met Office's Numerical Atmospheric-dispersion Modeling Environment (NAME) has been used to simulate the evolution of the ash cloud from the Eyjafjallajökull volcano during the initial phase of the ash emissions, 14–16 April 2010. NAME captures the timing and sloped structure of the ash layer observed over Leipzig, close to the central axis of the ash cloud. Relatively small errors in the ash cloud position, probably caused by the cumulative effect of errors in the driving meteorology en route, result in a timing error at distances far from the central axis of the ash cloud. Taking the timing error into account, NAME is able to capture the sloped ash layer over the UK. Comparison of the lidar observations and NAME simulations has allowed an estimation of the plume height time series to be made. It is necessary to include in the model input the large variations in plume height in order to accurately predict the ash cloud structure at long range. Quantitative comparison with the mass concentrations at Leipzig and Chilbolton suggest that around 3% of the total emitted mass is transported as far as these sites by small (<100 μm diameter) ash particles.

Validation of the FALL3D ash dispersion model using observations of the 2010 Eyjafjallajökull volcanic ash clouds

During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instru- ments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14e23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly- averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.